By Topic

Comments on "Asymptotic state tracking in a class of nonlinear systems via learning-based Inversion"

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jian-Xin Xu ; Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore ; Jing Xu

In the above paper, a learning approach to asymptotic state tracking for a class of nonlinear systems was proposed. The central idea of the approach is to first establish an equilibrium which is in essence an oscillatory steady-state, then incorporate a learning mechanism to eliminate the discrepancy between the desired and actual control. The paper presented a new analysis tool for the learning control problems, which is quite different from most existing tools developed insofar for learning control analysis. In this note, we would like to address some existing technical problems in the above paper, as well as the potential limitations in implementation.

Published in:

IEEE Transactions on Automatic Control  (Volume:51 ,  Issue: 4 )